Estimating the operational status of agents in distributed systems experiencing uncertain communication and agent attrition

This research introduces an estimation and decision making procedure for distributed multi-agent systems (DMAS) conducting cooperative missions in hostile environments. The focus of this research is to enable the DMAS to adapt to an uncertain and dynamic communication network. This work assumes that a DMAS operates with delayed communication and is vulnerable to experiencing communication faults in its network topology. Communication faults experienced by the DMAS are caused by enemy interference and can occur at random times. A communication fault is represented as either a temporary loss in an agent's transmitting and receiving capability, or agent attrition in which an agent becomes non-operational and is permanently removed from the system. The three novel techniques used in the proposed procedure include: i) a distributed linear Kalman filter to allow each agent to estimate pose information for itself and other system agents, ii) a process for distributively estimating the operational status of system agents by evaluating their communication times and estimated trajectories, and iii) a modified task allocation algorithm that incorporates the previously mentioned estimations so that the system can adapt to the changing network topology. Numerical results prove that utilizing the proposed procedure provides the DMAS with exceptional performance when operating in hostile environments where its communication network is susceptible to attack.